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cs.LG2022
Practical Insights of Repairing Model Problems on Image Classification
Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa
Additional training of a deep learning model can cause negative effects on the results, turning an initially positive sample into a negative one (degradation). Such degradation is…
cs.LG2022
NeuRecover: Regression-Controlled Repair of Deep Neural Networks with Training History
Shogo Tokui, Susumu Tokumoto, Akihito Yoshii +4
Systematic techniques to improve quality of deep neural networks (DNNs) are critical given the increasing demand for practical applications including safety-critical ones. The key…